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Simplified model to predict the thermal demand profile of districts

Talebi, Behrang; Haghighat, Fariborz; Mirzaei, Parham A.

Authors

Behrang Talebi

Fariborz Haghighat

Parham A. Mirzaei



Abstract

Extensive research works have been carried out over the past few decades in the development of simulation tools to predict the thermal performance of buildings. These validated tools have been used in the design of the building and its components. However, limited simulation tools have been developed for modeling of district energy systems, which can potentially be a very laborious and time-consuming process. Besides many associated limitations, providing a realistic demand profile of the district energy systems is not a straightforward task due to high number of parameters involved in predicting a detail demand profile.
This paper reports the development of a simplified model for predicting the thermal demand profile of a district heating system. The paper describes the method used to develop two types of simplified models to predict the thermal load of a variety of buildings (residential, office, attached, detached, etc.). The predictions were also compared with those made by the detailed simulation models.
The simplified model was then utilized to predict the energy demand of a variety of districts types (residential, commercial or mix), and its prediction accuracy was compared with those made by detailed model: good agreement was observed between the results.

Citation

Talebi, B., Haghighat, F., & Mirzaei, P. A. (2017). Simplified model to predict the thermal demand profile of districts. Energy and Buildings, 145, https://doi.org/10.1016/j.enbuild.2017.03.062

Journal Article Type Article
Acceptance Date Mar 25, 2017
Online Publication Date Apr 7, 2017
Publication Date Jun 15, 2017
Deposit Date Jun 30, 2017
Publicly Available Date Mar 29, 2024
Journal Energy and Buildings
Print ISSN 0378-7788
Electronic ISSN 1872-6178
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 145
DOI https://doi.org/10.1016/j.enbuild.2017.03.062
Keywords Simulation tool; District system; Community; Demand profile
Public URL https://nottingham-repository.worktribe.com/output/866165
Publisher URL http://www.sciencedirect.com/science/article/pii/S0378778817302104

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